Technology Readiness

The advancement of artificial intelligence (AI) and its growing societal importance are reshaping decision-making processes and policy analysis roles. This study examines the readiness of manufacturing companies in Malaysia to embrace AI technology, considering its potential to enhance decision-making, productivity, quality control, job automation, and data analysis. Focusing on the Technology, Organization, and Environment (T-O-E) readiness framework, the research investigates the relationship between these dimensions and AI adoption readiness among manufacturing companies in Shah Alam, Selangor, Malaysia. AI adoption readiness serves as the dependent variable, while technological, organizational, and environmental readiness dimensions act as independent variables. The study applies the T-O-E framework to AI readiness and proposes a framework for assessing AI readiness at the manufacturing level. It identifies factors influencing readiness within the technological, organizational, and environmental dimensions, including relative advantage, compatibility, resources, competitive pressure, top management support, and government regulations. Through rigorous analysis, patterns, trends, and correlations are revealed, highlighting a significant link between the T-O-E readiness dimensions and AI adoption readiness. Notably, organizational readiness emerges as a key driver of AI adoption in Malaysian manufacturing companies. The results of this investigation have broad implications, offering suggestions to improve organizational preparedness and unlock AI’s potential benefits for businesses in the industrial sector. Additionally, the research lays the groundwork for further studies on AI readiness across various industries and international contexts. As AI becomes increasingly integrated into manufacturing processes, adaptive businesses gain competitive advantages on a global scale. These advantages include increased productivity, informed decision-making, streamlined quality control, improved customer satisfaction, and potential contributions to economic growth. The study concludes by recommending strategies to reinforce organizational readiness and emphasizes the need for future research to deepen understanding of AI adoption readiness in the manufacturing industry. The integration of AI technology offers benefits such as enhanced productivity, decision-making, quality control, and customer satisfaction, granting businesses a competitive edge in the digital landscape and increasing stakeholder interest.

Purpose : Unlike human intelligence, which naturally exists, artificial intelligence (AI) is represented by human-like and non-human-like machines that are programmed by humans to serve human and commercial purposes. This technology enables computers to analyze complex data using sophisticated algorithms and mathematical models, allowing them to learn and improve autonomously. The main objective of this research is to examine the impact of AI stimuli and chatbots on smart customer experience and recommendatory marketing, considering the moderating role of technology readiness in platform businesses, based on the Stimulus-Organism-Response framework. Method : This study is classified as descriptive-survey research. Data were collected using a standard questionnaire. The statistical population consisted of users of the Snapp application. Due to the unlimited size of the population, G*Power software was applied for sample size determination. In total, 453 electronic questionnaires were collected, although 406 were required; analyses were conducted on the full set of 453 responses for greater reliability. Given the non-normal distribution of the data, Smart PLS version 4 and SPSS version 27 software were used for analysis. Findings : Of the 12 hypotheses tested, 9 were supported while 3 were rejected. Results confirmed the impact of enthusiasm, usability, and responsiveness on relative advantage and perceived interaction. Moreover, relative advantage and perceived interaction positively influenced recommendatory marketing. The moderating effect of optimism on the relationship between enthusiasm and perceived interaction was also supported. However, the moderating effect of feelings of lack of control on usability–relative advantage and enthusiasm–interaction relationships, as well as the moderating role of optimism on usability–relative advantage, were rejected. These results may be explained by the novelty of chatbot use in Iran and cultural differences. Conclusion : The findings indicate that AI-related stimuli, including chatbots, significantly affect the smart customer experience. In turn, perceived interaction and relative advantage influence recommendatory marketing. Organizations with proper infrastructure and sufficient human resources can therefore effectively leverage AI and chatbot capabilities.